Triple
T9857805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beauvechain |
E239630
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Jodoigne |
E347056
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Jodoigne | Statement: [Beauvechain, locatedNear, Jodoigne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jodoigne Context triple: [Beauvechain, locatedNear, Jodoigne]
-
A.
Jodoigne
chosen
Jodoigne is a historic town in Walloon Brabant, Belgium, known for its medieval architecture and role in regional agriculture.
-
B.
Mistinguett
Mistinguett was a famous French actress and singer of the early 20th century, celebrated as one of Paris’s most iconic music-hall stars.
-
C.
Elbling
Elbling is an ancient white wine grape variety primarily cultivated in Germany and Luxembourg, known for producing light, crisp, and high-acidity wines.
-
D.
Jodelet
Jodelet is a comic servant character in Molière’s play *Les Précieuses ridicules*, known for his rustic manners and humorous contrast with the pretentious protagonists.
-
E.
Tanguy
Tanguy is a French surname most notably associated with Yves Tanguy, a prominent 20th-century Surrealist painter.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca84e6493081909cf58c8d42ea856b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb399bd8081908281d1735cc3909f |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e43b2de881909e00f6701d1c7b54 |
completed | April 5, 2026, 4:25 a.m. |
Created at: March 30, 2026, 8:35 p.m.